As you said, independent variables are the ones that are manipulated by the researcher -- but that's assuming that the study is an experimental study in which the research is manipulating something. In a non-experimental study, nothing is manipulated. I non-experimental studies, the independent variable is the one used to form groups for comparison. For example: if you were doing a study comparing men and women, the independent variable would be "gender." If you were comparing people over 65 years old and people under 65 years old, the independent variable would be "age group." Does that make sense?
"Extraneous variable" is a general term for those variables (factors) in the environment that may or may not effect the study's results. For example, the time of day the data was collected, the weather, the color of shirt worn by the researcher, the background noise in the room while the person filled out a survey, etc. These things MAY have influenced the results, but you don't know that. A really good researcher identifies those variables and tries to determine if they had and influence or not ... and tries to control for them as much as possible just in case they do have an influence.
"Confounding variables" are those variables (that might have first been thought of extraneous variables) that are found to have actually influenced the results. For example: Sometimes the age of the participants makes a difference in a study's results ... or their educational level ... etc.
Not every researcher discusses all of the extraneous variables and/or confounding variables in any detail. Sometimes, that discussion gets omitted from the publication to save space in the article. And of course, some researchers do a better job than others in identifying and considering all of those other variables as they conduct their study in the first place.
I hope that helps.